Behaviorists place "an emphasis on producing observable and measurable
outcomes in students" (Ertmer & Newby, 1993, p. 56). They believe that
learning occurs when learners show the correct response to a certain stimulus
(Smith & Ragan, 1999). The current instructional design application of behavioral
objectives is reminiscent of these behaviorist views. However, most current
instructional designers writing objectives based on action do not share the
behaviorists' disinterest in the cognitive processes that also take place. Rather,
they write objectives with an attempt to extract "best evidence" of
the cognitive processes that cannot be directly observed.

Walter Dick and Lou Carey (1996) advocate a systems approach model for designing
instruction in the fourth edition of their text, The Systematic Design of
Instruction. Their work is based on the behaviorist view that there is a
predictable link between a stimulus and the response it produces in a learner
(Colaric, n.d.). It is the designer's responsibility to determine the sub-skills
a student must master in order for the behavior to be learned and choose the
stimulus and strategy for instruction in order to assemble the sub-skills. The
basic steps in the Dick and Carey instructional design model are as follows:

The idea of assessing students based on observable performance started with
behaviorism. According to Ertmer & Newby (1993), "Behaviorism equates
learning with changes in either the form or frequency of observable performance"
(p. 55). Once a student can display the proper response following the presentation
of a certain environmental stimulus, learning has been achieved. Traditional
behaviorist assessment makes no evaluation of the knowledge structure or mental
processes leading to a student's response.

Criterion-referenced assessment, which measures what a student can do as compared
to behavior described in specific learning objectives (Smith & Ragan, 1999),
is based on behaviorist principles. Such assessment is used to determine a student's
individual competency in skills defined as goals for instruction, as opposed
to rank them with other learners.

Behaviorist theories contributed to the development of "more efficient
methods of creating directed instruction" (Roblyer, Edwards & Havriluk,
1996, p. 62). Systems models take information from learning theories and turn
them into step-by-step procedures for planning instruction. Systems models were
developed in response to problems teachers were having in satisfying the needs
of large numbers of students. According to Saettler (1990) these models were
initially embraced more by military and industrial trainers than by K-12 classroom
teachers. While systems approaches are heavily used in the design and development
of self-contained tutorials, teachers can also use the same approach to plan
their own directed instruction with technology. Systems models can help teachers
evaluate the effectiveness of their own teaching as well as the usefulness of
computer-based resources. Most instructional design models and methods are rooted
in systems models.

Cognitive psychology has influenced the types of goals and objectives that
are developed as a result of task analysis (Smith
& Ragan, 1999). In addition to observable performance, attention is now
given to the underlying "understanding" of a performance. For example,
an objective might specify that a learner should be able to explain the reasoning
behind his/her performance. Bloom's
taxonomy addresses the cognitive domain.

Cognitivists conduct learner analyses to determine a learner's predisposition
to learning and decide how to design instruction so that is can be assimilated
according to the learner's existing mental structures (Ertmer & Newby, 1993).
Learner characteristics are considered when a designer plans what instructional
techniques, called learning strategies, to use in the instruction (Smith &
Ragan, 1999). Strategies that focus on structuring, organizing, and sequencing
information for optimal processing are based on cognitivism. For example, outlining,
summarizing, synthesizing, and advance organizers.

Robert Gagne, among others who developed taxonomies, made one of the first
attempts to classify learning behaviors and supply specific measures for determining
different levels of learning. Gagne developed a taxonomy for intellectual
skills, one of his five learned capabilities. Closely related to the development
of taxonomies are instructional objectives and instructional systems design.

A prerequisite is something a person must know or be able to do before they
are able to learn something else (Smith & Ragan, 1999). To determine prerequisite
information, an analysis must be done from the learner's (novice's) perspective,
rather than the expert's perspective. An expert tends to overlook some of the
things they needed to know in order to achieve the learning goal. Determining
prerequisite skills does not specify instructional strategies. An analysis for
prerequisites can be used for a top-down, problem-based environment as well
as a bottom-up structured instructional strategy.

With the shift to cognitivism, analysis of relevant concepts goes beyond behavioral
observations of job performance. "Content analysis has outgrown the mere
listing of statements the learner will be able to recite. It has advanced way
beyond the old conventions of S-R tables" (Tiemann and Markle, 1984, p.
26).

During task analysis, goal
statements are transformed into a format that can be used to guide the rest
of the instructional design process (Smith & Ragan, 1999). To complete a
learning task analysis:

Write a learning goal.

Determine the types of learning of the goal.

Conduct an information-processing analysis of that goal.

Conduct a prerequisite analysis and determine the type of learning of the
prerequisites.

Write learning objectives for the learning goal and each of the prerequisite
(p. 63).

Upon completion of a task analysis, the designer has a list of goals describing
what learners should know or be able to do upon completion of instruction, as
well as the prerequisite skills an knowledge needed to achieve those goals.

As a result of the change in goals and methods of education, constructivist
learning environments tend to use more qualitative assessment strategies rather
than quantitative ones (Roblyer, Edwards & Havriluk, 1996). For example,
one of the more popular ways to assess students in a constructivist learning
environment is through portfolios. Portfolios consist of samples of students'
work and products developed. A portfolio might also include teacher narration
describing students' work habits, strengths and weaknesses. Performance-based
assessments and checklists of criteria used to judge students' performance might
also be included (Linn, 1994).

According to Wiggins (1990), "Assessment is authentic when we directly
examine student performance on worthy intellectual tasks" (par. 1). Assessments
should be built on intellectual challenges such as problem-solving, experimental
research, discussion, and writing. Furthermore, the goal of assessment is primarily
to support the needs of the learner. The best tests should teach students the
type of work that matters most.

While constructivists differ among themselves about how much guidance a teacher
should provide, all agree that there should be some flexibility in achieving
desired goals (Roblyer, Edwards & Havriluk, 1996). Most constructivist approaches
emphasize exploration over "getting the right answer." A few of the
radical constructivists believe that students should have total freedom and
infinite time when it comes to learning through exploration. However, Perkins
(1991) states, "Education given over entirely to WIG (without any given)
instruction would prove grossly inefficient and ineffective, failing to pass
on in straightforward ways the achievements of the past" (p. 20).

Students solving problems, whether in a specific content area or in an interdisciplinary
approach, is the focus of most constructivist models (Roblyer, Edwards &
Havriluk, 1996). For example, one problem might require students to use only
math skills, while another might require math, science and language arts skills.
According to Jungck (1991) constructivist methods often integrate problem posing,
problem solving and "persuasion of peers" (p. 155). Furthermore, problems
can be presented with specific goals, as "what if" questions or as
open-ended questions. Problem solving in a constructivist learning environments
is usually more complex and demands more time and use of varied skills than
problem solving with directed instruction.

Most constructivist approaches advocate what Perkins (1991) terms "richer
learning environments" (p. 19) as opposed to the "minimalist"
classroom environment, which depends on the teacher, textbooks and prepared
materials (Roblyer, Edwards & Havriluk, 1996). According to Perkins, most
constructivist models use any combination of the following five basic resources.

Cognition and Technology Group at Vanderbilt (CTGV) is a strong advocate of
helping students build good "mental models" of problems to be solved
(Roblyer, Edwards & Havriluk, 1996). To promote the use of these mental
models, teachers should present problems in visual rather than written formats.
CTGV researchers (1990) say, "Visual formats allow students to develop
their own pattern recognition skills," and they are "dynamic, rich
, and spatial" (p. 3). The use of visual formats may be particularly important
for low-achieving students who have difficulty reading.